Permanent magnet synchronous machines (PMSMs) are used in many high performance applications. For vector control of PMSMs, information on the rotor position is required. In sensorless control, the rotor speed and position can be estimated by fundamental-excitation methods as in [1] R. Wu and G. R. Slemon, “A permanent magnet motor drive without a shaft sensor,” IEEE Trans. Ind. Applicat., vol. 27, no. 5, pp. 1005-1011, September/October 1991 or signal injection methods as in [2] P. L. Jansen and R. D. Lorenz, “Transducerless position and velocity estimation in induction and salient AC machines,” IEEE Trans. Ind. Applicat., vol. 31, no. 2, pp. 240-247, March/April 1995.
The above methods can also be combined by changing the estimation method as the rotor speed varies, as disclosed in [3] A. Piippo, M. Hinkkanen, and J. Luomi, “Sensorless control of PMSM drives using a combination of voltage model and HF signal injection,” in Conf. Rec. IEEE-IAS Annu. Meeting, vol. 2, Seattle, Wash., October 2004, pp. 964-970. The fundamental-excitation methods used for sensorless control are based on models of the electrical subsystem, i.e. the permanent magnet machine. Hence, the electrical parameters are needed for the speed and position estimation as disclosed in [4] K.-H. Kim, S.-K. Chung, G.-W. Moon, I.-C. Baik, and M.-J. Youn, “Parameter estimation and control for permanent magnet synchronous motor drive using model reference adaptive technique,” in Proc. IEEE IECON'95, vol. 1, Orlando, Fla., November 1995, pp. 387-392. The erroneous stator resistance results in an incorrect back-emf estimate, and consequently, impaired position estimation accuracy. The operation can also become unstable at low speeds in a loaded condition. The stator resistance depends on the motor temperature, and an adaptation scheme for the resistance is thus required to improve the estimation accuracy.
Several methods have been proposed to improve the performance of a PMSM drive by estimating the electrical parameters. An MRAS scheme is used for the on-line estimation of the stator resistance in sensorless control [4]. A DC-current signal is injected to detect the resistive voltage drop for the resistance estimation in document [5] S. Wilson, G. Jewell, and P. Stewart, “Resistance estimation for temperature determination in PMSMs through signal injection,” in Proc. IEEE IEMDC'05, San Antonio, Tex., May 2005, pp. 735-740. The stator resistance and the permanent magnet flux are estimated in sensorless control in [6] K.-W. Lee, D.-H. Jung, and I.-J. Ha, “An online identification method for both stator resistance and back-emf coefficient of PMSMs without rotational transducers,” IEEE Trans. Ind. Electron., vol. 51, no. 2, pp. 507-510, April 2004. The estimation in [6] is carried out using both the steady-state motor equations and response to an alternating current signal. However, the convergence of the estimated parameters to their actual values is not shown.
A method for extracting the resistance and the inductances of a salient PMSM from an extended EMF model is proposed in [7] S. Ichikawa, M. Tomita, S. Doki, and S. Okuma, “Sensorless control of permanent-magnet synchronous motors using online parameter identification based on system identification theory,” IEEE Trans. Ind. Electron., vol. 53, no. 2, pp. 363-372, April 2006. Three electrical parameters are estimated simultaneously, but the experimental results depict vague behavior of the stator resistance estimate.
The problem relating to the known resistance estimation methods is the inaccuracy of the estimated resistance value. If the resistance is estimated prior to the use, its value will be accurate only at certain temperatures. It would thus be desirable to obtain an on-line resistance adaptation scheme that would keep the resistance estimate correct despite of the variations in the temperature.